Smaller Australian raptors have greater urban tolerance

Urbanisation is occurring around the world at a rapid rate and is generally associated with negative impacts on biodiversity at local, regional, and global scales. Examining the behavioural response profiles of wildlife to urbanisation helps differentiate between species that do or do not show adaptive responses to changing landscapes and hence are more or less likely to persist in such environments. Species-specific responses to urbanisation are poorly understood in the Southern Hemisphere compared to the Northern Hemisphere, where most of the published literature is focussed. This is also true for raptors, despite their high diversity and comparably high conservation concern in the Southern Hemisphere, and their critical role within ecosystems as bioindicators of environmental health. Here, we explore this knowledge gap using community science data sourced from eBird to investigate the urban tolerance of 24 Australian raptor species at a continental scale. We integrated eBird data with a global continuous measure of urbanisation, artificial light at night (ALAN), to derive an urban tolerance index, ranking species from positive to negative responses according to their tolerance of urban environments. We then gathered trait data from the published literature to assess whether certain traits (body mass, nest substrate, habitat type, feeding guild, and migratory status) were associated with urban tolerance. Body size was negatively associated with urban tolerance, as smaller raptors had greater urban tolerance than larger raptors. Out of the 24 species analysed, 13 species showed tolerance profiles for urban environments (positive response), and 11 species showed avoidance profiles for urban environments (negative response). The results of this study provide impetus to conserve native habitat and improve urban conditions for larger-bodied raptor species to conserve Australian raptor diversity in an increasingly urbanised world.


Methods and materials
Raptor observation data. We used observations of raptors across continental Australia from eBird 60,61 , a long-running community science project spanning the globe. Checklists of birds seen and heard are submitted by volunteer birdwatchers, along with user effort variables, such as survey duration, distance travelled, and spatiotemporal information, which are all recorded manually or by a phone application 75 . Since eBird began in 2002, users have submitted over 89 million checklists, amounting to over 1.2 billion observations of birds worldwide, making it one of the largest and most successful community science projects to date.
The eBird basic dataset for Australia (ver. ebd_rel_AU_Jun-2021; available at: https:// ebird. org/ data/ downl oad) was downloaded and all observations of raptors between 1 January 2010 and 30 June 2021 were used, as the vast majority of submitted checklists lie within this period (> 95%). As the aim of this study was to identify Scientific Reports | (2023) 13:11559 | https://doi.org/10.1038/s41598-023-38493-z www.nature.com/scientificreports/ Australian raptor tolerance to urban environments at a broad temporal and spatial scale rather than examining changes between years, pooling the data over many years to include the largest amount possible was necessary to achieve this outcome. Checklists were filtered according to the eBird best practices guide recommendations 76 to minimise the bias often present in community science datasets 77 . We filtered the data to include only 'complete' checklists-a case where the user had submitted a checklist of all the bird species they had seen/heard. Checklists that were 'Stationary' or 'Travelling' or followed Birdlife Australia survey protocols such as 'Birdlife Australia 20 min-2 ha survey' , 'Birdlife Australia 500 m radius search' or 'Birdlife Australia 5 km radius search' were included, while checklists where the observer travelled for greater than 5 h or over 5 kms were removed to reduce observer variation effort 78 .
Ecological traits. Ecological traits were selected from the existing literature that may influence avian tolerance to urban environments 54,56 . Data for body mass, nest substrate, habitat type, feeding guild, and migratory status were compiled from information found in the dataset 'Biological, ecological, conservation and legal information for all species and subspecies of Australian bird' 79 79,83 . We used the definition of local dispersal and partially migrant from 79 , and these definitions can be found in Table 1 in the 'migratory status' section.

Measure of urbanisation.
To quantify the relationship between species occurrence and the urban environment, we used VIIRS night-time lights 84 data as a proxy for urban areas. It is a continuous measure readily available for download through Google Earth Engine 85 that correlates positively with human population density 86,87 and that is frequently used as a measure of urbanisation in ecological studies 13,[88][89][90] . Whilst other measures of urbanisation exist 91,92 (e.g. impervious surface cover, skyglow), we chose this method due to its ability to produce a continuous estimate that can individually rank species rather than placing species into arbitrary categories. Our choice was also driven by the fact that the available data existed mostly within the timeframe of this study at the appropriate spatial grain. The data product comes pre-filtered from sources of background noise such as degraded data, fires, and light source contamination for maximum precision. To obtain the median radiance value for each checklist, monthly rasters of the VIIRS night-time lights were combined from 1 January 2014 to 31 December 2020 to create a single raster in Google Earth Engine. This raster was imported into R 93 , where the median radiance was extracted within a 5-km buffer of each checklist. The ALAN median radiance values were condensed between 2014 and 2020 into a single value as exploratory analysis showed there were no large differences between years of a random sample of 1,000 distinct localities.
Statistical analysis. Analyses were conducted using the statistical software R (v4.2) in the integrated RStudio environment 93 . The tidyverse workflow was used for data manipulation 94 , and the ggplot2 package 95 was used for figure plotting. To eliminate records where the birds were unlikely to occur and remove any unusual records, species checklists were cropped to the extent of their known ranges using shapefiles from the 'Birds of the World' dataset from Birdlife International 96 using the sf package 97 , which is a common technique used within ecological studies 98,99 . Hexagonal grids of 5 km width were generated across mainland Australia using the dggridR package 100 to facilitate spatiotemporal sub-sampling, a commonly used technique to remove potential spatial www.nature.com/scientificreports/ and temporal bias, as well as class imbalance (more non-detections than detections of focal species), within community science data 78,101 . Prior to modelling, one checklist was sampled from each grid cell from every week of the year across all available years (2010-2021) to remove any spatiotemporal bias, and detection and nondetection were sampled independently to deal with any class imbalance and ensure that not too many detections were lost. Exploratory modelling was then undertaken on all species; species under 1000 checklists with at least 1 observation produced large confidence intervals of their urban tolerance profile relative to the other species and were therefore excluded from the analysis. This reduced the initial set of 34 mainland Australian raptors to the final set of 24 candidate species for modelling (Supplementary material A2).
To examine urban tolerance in Australian raptors, generalised additive models (GAMs) were used with a negative binomial error structure to account for over-dispersion within the data. The eBird best practices guide 76 was used as guidance for model preparation and fitting. The response variable for each model was the estimated abundance of each species within the checklist, while the predictor variable was the median VIIRS night-time lights value assigned to each checklist. Smoothing functions were applied to variables that were likely to influence the detection of a species on a checklist: number of observers, latitude and longitude, duration (min), day of year, effort distance (km) and 'time observations started' . Thin plate regression splines were used for the variables: number of observers, latitude and longitude, duration (min), day of year, effort distance (km) with four degrees of freedom, and a cyclic cubic regression spline was used for 'time observation started' with 5 degrees of freedom. For each species' model, the parameter estimate for night-time lights was obtained, indicating the relationship each species had with urbanisation (i.e. positive or negative) and the magnitude of that relationship. To reduce the uncertainty of the measure of urban tolerance due to the random sampling of eBird checklists within a grid cell, we ran our analysis 100 times for each species to obtain an average parameter estimate.
Multiple linear regression (i.e., all variables included in one model simultaneously) was used to investigate which ecological traits were associated with the species' response to urbanisation, accounting for all other traits. The response variable was the species response to urbanisation (i.e. parameter estimate) extracted from the GAMs, while the predictor variable was the value of the five traits for each raptor (body mass, nest substrate breadth, habitat breadth, feeding guild, and migratory status) ( Table 1). All quantitative predictor variables were scaled and centred prior to linear regression modelling, and visual inspection of residuals for model validation was undertaken.

Results
A total of 840,918 eBird checklists were analysed, using 364,074 observations from 24 species prior to spatiotemporal subsampling, where one checklist was sampled across each 5 × 5 km grid from a species distribution range per week (Fig. 1). Spatio-temporal subsampling reduced the total number of species observations to 276,674. The Whistling Kite (Haliastur sphenurus) was detected the most of any raptor in the study, amassing 45,787 observations, while the Eastern Barn Owl (Tyto alba) was observed the fewest times, recorded on 1051 occasions across checklists (Supplementary material A2). Detection rates across sampled grids and the respective distributions of the study species can be found within the supplementary material (A3). The raptors observed in the area with the highest median radiance, or the brightest area across the study region, were the Brown Goshawk (Accipiter fasciatus) and Southern Boobook (Ninox boobook) (103.107 nW cm −2 sr −1 ) in Docklands Park, adjacent the Yarra River in central Melbourne, Victoria. A Whistling Kite was sighted in the area with the lowest median radiance (0.062 nW cm −2 sr −1 ), or the darkest area across the study region, which was at Lagoon Island, Lake Argyle, in north-eastern Western Australia.
From the 24 raptor species included in the analysis, 13 species displayed a positive response and 11 species showed a negative response to urbanisation. The species with the highest tolerance to urbanisation were the Eastern Barn Owl and the Australian Hobby (Falco longipennis), while the Brown Falcon (Falco berigora) and the Wedge-tailed Eagle (Aquila audax) were the least tolerant raptor species to urban areas (Fig. 2).

Discussion
We assessed the urban tolerance of 24 Australian raptor species, whereby 13 showed a positive response to artificial light at night and 11 species showed a negative response. This finding highlights species-specific differences in urban tolerance across the Australian continent 13 , with some raptors showing tolerance response profiles in urban areas and others showing avoidance response profiles. Furthermore, body size was the main trait explaining the species-specific urban tolerance score, as smaller raptors were more likely to have greater urban tolerance index scores than larger raptors. Our results show the wide range in raptor tolerance response to urban environments, measured here using artificial light at night. Given that urban sprawl continues to develop across Australia, understanding the tolerance profiles of different raptor species to environmental change is vital information to inform conservation strategies for human-modified landscapes.
The Brahminy Kite (Haliastur indus) was found to be the most tolerant Australian raptor to urbanisation. Brahminy Kites are a coastal raptor, commonly seen soaring along the shoreline, as well as scavenging for food on beaches and jetties 80 80 . Additionally, they also showcase a generalist diet which comprises of fish, birds, reptiles, crustaceans, amphibians, mammals, insects and offal 80,102 , which allows it to exist within a wide variety of different environmental conditions. The ability of Brahminy Kites to breed within urban areas highlights their capacity to tolerate human disturbance, but with increasing levels of urbanisation on the coast of Australia, there is an increased risk of poisoning from feral animal control and ingestion and entanglement from fishing equipment 103 . At the other end of the urban tolerance spectrum is the Wedge-tailed Eagle, the raptor with the lowest urban tolerance score. The species is known to be highly sensitive to human disturbance 105 and to avoid urban landscapes. For example, human activity from mountain bikers, off-road vehicles and bushwalkers has the potential to impact breeding success in Wedge-tailed Eagles that are located close to urban areas in Perth, Western Australia 106 . Wedge-tailed Eagles will retreat from urban expansion 107 , however, some individual pairs show a higher disturbance tolerance to human activity when breeding inside protected reserves 108 . The finding that larger raptors have lower urban tolerance than smaller species is consistent with findings from other studies investigating urban raptor occurrence 54,55 . One particular study undertaken in Reno-sparks, Nevada, USA, showed that Golden Eagles (Aquila chrysaetos) breed the furthest away from urban development when compared to other smaller species, and the authors concluded that habitat requirements (e.g. large, open terrain) and life history traits (e.g. small clutch sizes, long-post-fledging dependency) likely explained this result 109 . In our study, Australia's largest birds of prey, the Wedge-tailed Eagle, and White-bellied Sea-Eagle (Haliaeetus leucogaster), were both found to avoid urban areas. Given that body size usually correlates with life history 'speed' 110 , this negative correlation between urbanisation and eagle occurrence might have a similar explanation to the one reported for Golden Eagles 108,111 . Wedge-tailed Eagles usually nest several kilometres away from human developments 105,108,112 , while White-bellied Sea-Eagles can occasionally nest within urban green space 113 using forested zones scattered throughout the metropolitan area 114 117 , whereby the larger the species, the higher the potential for exposure to anthropogenic threats and conservation concern. This association between body size and conservation status highlights the need to safeguard suitable habitat outside of cities to meet the requirements for large raptor species in the future. In Australia, raptors with smaller body mass (172 g to 370 g) were generally tolerant of urbanisation, while medium-sized raptors (548 g to 847 g) displayed a variable response (e.g. tolerant or avoidant) to urbanisation. A potential driver of this trend may be the distribution of suitable prey residing within and outside urban areas, which can be linked to body size. Avian specialists are known to thrive in urban areas 21 , as they profit from an increased density of avian prey attracted to supplementary food sources such as bird feeders 118,119 , which are a  Table 2. Model summaries of the association between ecological traits of 24 Australian raptor species and their urban tolerance index for multiple regression linear modelling, including estimate, standard error (SE), t-value, lower and upper confidence limits. The confidence interval is reported at the 95% level. The reference category for feeding guild was generalist, and the reference category for migratory status was Local dispersal. Multiple r-squared-0.4413.

Term
Estimate SE T-value Lower confidence interval limit Upper confidence interval limit  125,126 , as well as exotic shrubs and flowers planted in gardens 127 , that can provide nectar all year round 128 for species such as honeyeaters and parrots 129 upon which raptors can feed on. Many of the raptors with a moderate body mass are diet generalists, such as the Brahminy Kite and Spotted Harrier (Circus assimilis). These species displayed markedly different urban tolerance profiles, which could be a function of the distribution of their prey existing either inside or outside of urban habitat. However, habitat preferences may also play a role in this phenomenon, and therefore further research is needed to clarify the link between Australian raptors of medium body size and urban tolerance and the underlying mechanisms driving the pattern. Partially migrant and sedentary species had similar urban tolerance profiles, which is consistent with the findings from recent studies focussing on raptors across the globe 54 and in Argentina 130 . Little Eagles (Hieraaetus morphnoides) are partially migratory, usually migrating from Southern Australia to Northern Australia during the winter months 131 . Ongoing GPS tracking studies have confirmed that the habitats used by breeding Little Eagles www.nature.com/scientificreports/ in Canberra were similar to those used during migration (woodland, grassland, forested areas, open urban land), and they appear to be tolerant of human activity and urban landscapes regardless of their breeding or migration state 132 . Booted Eagles (H. pennatus), a close relative of the Little Eagle, also showed positive responses to urban landscapes, as a population increase in western Europe was observed due to an increase in suitable prey 133 .
Ongoing monitoring of raptor migration will be important to locate key areas used by urban-adapted species, potentially also as suitable stop-over spots during migration, to ensure their conservation.

Study limitations.
While large-scale data collection by community scientists can facilitate continentalwide data, we acknowledge that such data face several limitations. For example, owls are nocturnal hunters, well camouflaged and cryptic in nature, which results in a lower detectability that often relies on identification by call rather than a visual confirmation. Sightings of owls may be more biased towards brighter urban areas, as artificial light sources such as streetlights and industrial lighting could enable easier observation. A clustered detectability may be apparent because of known roost sites, and in combination with some observers (i.e. birders) keen to take advantage of ticking off a target species, can lead to an over-representation of one single individual in an area 134 .
We also recognize that most of the Australian population lives coastally, and therefore checklists are heavily biased towards these areas and along main highways connecting inhabited regions. Even though spatiotemporal sub-sampling was used to mitigate such biases, such clustering of observations still occurred, especially in data rich areas. But, as raptors were the only taxa investigated in this study, which are usually detected using the same methods and the observations are subject to the same biases, it is probable that the systematic sampling bias is analogous for all species observed in this study 13,135 . ALAN was used as a continuous metric of urbanisation within this study, and whilst this measure of urbanisation correlates positively with human population density and impervious surface cover 136,137 , urbanisation occurs across large spatial scales, from the landscape to the local level 138 . Therefore, it is likely that across these scales species responses to urbanisation may differ 139 , and the results from this study reflect Australian raptor responses to urbanisation at a broad scale rather than a fine scale, with the limitation that ALAN was used as a proxy for urbanisation. However, while ALAN is a proxy for urbanisation, it could also serve as a sensory pollutant for raptors, impacting the biological clocks of raptors and their prey. For example, owl species in this study could use night-time lighting as artificial hunting hot spots where prey may congregate to the lights, whereas larger species such as eagles may avoid well-lit areas due to their sensitivity to anthropogenic disturbance. To assess urban tolerance more accurately at finer scales, rather than the broad-scale approach like we have used here, data from GPS-tracked birds or survey data assessing the occupancy of birds in urban areas in conjunction with high-resolution landcover data would be a more suitable approach. Further, the results showed that body mass was the only trait that significantly influenced urban tolerance in Australian raptors, and no other traits influenced urban tolerance. The non-significance of the other traits may have been because of the coarse resolution that the traits were selected at (e.g. continental Australia). To be reliable, generally functional traits need to be location and individual specific 140 , however when working at the macroecological scale and assessing interspecific differences, coarser trait resolution is suitable 141 . As we were assessing tolerance at the landscape level, we chose to select traits at a coarse scale as it was the most useful resolution for this study, but we acknowledge that the reliability of these traits across time and space for some species may be significantly decreased.
Future areas of study. The eBird checklist numbers in Australia are growing more numerous each year, and therefore investigations into the urban tolerance of raptor species that occur at lower densities (e.g. Red Goshawk) may become feasible in the future, most likely in conjunction with targeted surveys from conservation related organisations. Also, a more granular examination of habitat use within urban areas of urban tolerant raptors will be an important area of future research to conserve important foraging and breeding areas. Such approaches will help identify which raptor species are occupying urban areas during the breeding season, and those that only visit to forage or roost.

Conclusion
In summary, this research used a large continent-wide raptor data set collected by community scientists and professional birders across Australia to generate valuable insights into the urban tolerance of 24 Australian raptor species. The finding that the 13 species with greater urban tolerance also had, on average, smaller body size, sheds light on mechanistic pathways that may be driving urban tolerance response profiles. Smaller-bodied species tend to have faster life histories and higher metabolic rates, producing larger clutches earlier in life that are frequently provisioned with relatively small prey. The abundance and commonality of nocturnal and diurnal prey including small mammals, rodents, pigeons, doves, and passerines, in conjunction with the diet speciality of many small Australian raptors, may favour the persistence and survival of smaller-bodied raptors in urban environments. Conservation management initiatives, particularly those that focus on habitat preservation and restoration (e.g. wilderness area protection), are needed with a special focus on protecting larger-bodied raptor species given urban expansion and an avoidance response of larger raptor species to urban areas.